{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "\n",
    "## GeostatsPy: Basic Univariate Statistics and Distribution Representativity for Subsurface Data Analytics in Python \n",
    "\n",
    "\n",
    "### Michael Pyrcz, Associate Professor, University of Texas at Austin \n",
    "\n",
    "#### [Twitter](https://twitter.com/geostatsguy) | [GitHub](https://github.com/GeostatsGuy) | [Website](http://michaelpyrcz.com) | [GoogleScholar](https://scholar.google.com/citations?user=QVZ20eQAAAAJ&hl=en&oi=ao) | [Book](https://www.amazon.com/Geostatistical-Reservoir-Modeling-Michael-Pyrcz/dp/0199731446) | [YouTube](https://www.youtube.com/channel/UCLqEr-xV-ceHdXXXrTId5ig)  | [LinkedIn](https://www.linkedin.com/in/michael-pyrcz-61a648a1)\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### PGE 383 Exercise: Basic Univariate Summary Statistics and Data Distribution Representativity Plotting in Python with GeostatsPy\n",
    "\n",
    "Here's a simple workflow with some basic univariate statistics and distribution representativity. This should help you get started data declustering to address spatial sampling bias.\n",
    "\n",
    "#### Geostatistical Sampling Representativity\n",
    "\n",
    "In general, we should assume that all spatial data that we work with is biased.\n",
    "\n",
    "##### Source of Spatial Sampling Bias\n",
    "\n",
    "Data is collected to answer questions:\n",
    "* how far does the contaminant plume extend? – sample peripheries\n",
    "* where is the fault? – drill based on seismic interpretation\n",
    "* what is the highest mineral grade? – sample the best part\n",
    "* who far does the reservoir extend? – offset drilling\n",
    "and to maximize NPV directly:\n",
    "* maximize production rates\n",
    "\n",
    "**Random Sampling**: when every item in the population has a equal chance of being chosen. Selection of every item is independent of every other selection.\n",
    "Is random sampling sufficient for subsurface?  Is it available?\n",
    "* it is not usually available, would not be economic\n",
    "* data is collected answer questions\n",
    "    * how large is the reservoir, what is the thickest part of the reservoir \n",
    "* and wells are located to maximize future production\n",
    "    * dual purpose appraisal and injection / production wells!\n",
    "\n",
    "**Regular Sampling**: when samples are taken at regular intervals (equally spaced).  \n",
    "* less reliable than random sampling.\n",
    "* Warning: may resonate with some unsuspected environmental variable.\n",
    "\n",
    "What do we have?\n",
    "* we usually have biased, opportunity sampling \n",
    "* we must account for bias (debiasing will be discussed later)\n",
    "\n",
    "So if we were designing sampling for representativity of the sample set and resulting sample statistics, by theory we have 2 options, random sampling and regular sampling.\n",
    "\n",
    "* What would happen if you proposed random sampling in the Gulf of Mexico at $150M per well?\n",
    "\n",
    "We should not change current sampling methods as they result in best economics, we should address sampling bias in the data.\n",
    "\n",
    "Never use raw spatial data without access sampling bias / correcting.\n",
    "\n",
    "##### Mitigating Sampling Bias\n",
    "\n",
    "In this demonstration we will take a biased spatial sample data set and apply declustering using **GeostatsPy** functionality.\n",
    "\n",
    "#### Objective \n",
    "\n",
    "In the PGE 383: Stochastic Subsurface Modeling class I want to provide hands-on experience with building subsurface modeling workflows. Python provides an excellent vehicle to accomplish this. I have coded a package called GeostatsPy with GSLIB: Geostatistical Library (Deutsch and Journel, 1998) functionality that provides basic building blocks for building subsurface modeling workflows. \n",
    "\n",
    "The objective is to remove the hurdles of subsurface modeling workflow construction by providing building blocks and sufficient examples. This is not a coding class per se, but we need the ability to 'script' workflows working with numerical methods.    \n",
    "\n",
    "#### Getting Started\n",
    "\n",
    "Here's the steps to get setup in Python with the GeostatsPy package:\n",
    "\n",
    "1. Install Anaconda 3 on your machine (https://www.anaconda.com/download/). \n",
    "2. From Anaconda Navigator (within Anaconda3 group), go to the environment tab, click on base (root) green arrow and open a terminal. \n",
    "3. In the terminal type: pip install geostatspy. \n",
    "4. Open Jupyter and in the top block get started by copy and pasting the code block below from this Jupyter Notebook to start using the geostatspy functionality. \n",
    "\n",
    "You will need to copy the data file to your working directory.  They are available here:\n",
    "\n",
    "* Tabular data - sample_data_biased.csv at https://git.io/fh0CW\n",
    "\n",
    "There are exampled below with these functions. You can go here to see a list of the available functions, https://git.io/fh4eX, other example workflows and source code. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import geostatspy.GSLIB as GSLIB          # GSLIB utilies, visualization and wrapper\n",
    "import geostatspy.geostats as geostats    # GSLIB methods convert to Python        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will also need some standard packages. These should have been installed with Anaconda 3."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np                        # ndarrys for gridded data\n",
    "import pandas as pd                       # DataFrames for tabular data\n",
    "import os                                 # set working directory, run executables\n",
    "import matplotlib.pyplot as plt           # for plotting\n",
    "from scipy import stats                   # summary statistics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Set the working directory\n",
    "\n",
    "I always like to do this so I don't lose files and to simplify subsequent read and writes (avoid including the full address each time). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir(\"c:/PGE383\")             # set the working directory"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Loading Tabular Data\n",
    "\n",
    "Here's the command to load our comma delimited data file in to a Pandas' DataFrame object.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('sample_data_biased.csv')     # load our data table (wrong name!)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "No error now! It worked, we loaded our file into our DataFrame called 'df'. But how do you really know that it worked? Visualizing the DataFrame would be useful and we already leard about these methods in this demo (https://git.io/fNgRW). \n",
    "\n",
    "We can preview the DataFrame by printing a slice or by utilizing the 'head' DataFrame member function (with a nice and clean format, see below). With the slice we could look at any subset of the data table and with the head command, add parameter 'n=13' to see the first 13 rows of the dataset.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     X    Y  Facies  Porosity       Perm\n",
      "0  100  900       1  0.115359   5.736104\n",
      "1  100  800       1  0.136425  17.211462\n",
      "2  100  600       1  0.135810  43.724752\n",
      "3  100  500       0  0.094414   1.609942\n",
      "4  100  100       0  0.113049  10.886001\n"
     ]
    },
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Facies</th>\n",
       "      <th>Porosity</th>\n",
       "      <th>Perm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>100</td>\n",
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       "      <th>2</th>\n",
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       "      <td>0.094414</td>\n",
       "      <td>1.609942</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>0.113049</td>\n",
       "      <td>10.886001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>200</td>\n",
       "      <td>800</td>\n",
       "      <td>1</td>\n",
       "      <td>0.154648</td>\n",
       "      <td>106.491795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>200</td>\n",
       "      <td>700</td>\n",
       "      <td>1</td>\n",
       "      <td>0.153113</td>\n",
       "      <td>140.976324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>200</td>\n",
       "      <td>500</td>\n",
       "      <td>1</td>\n",
       "      <td>0.126167</td>\n",
       "      <td>12.548074</td>\n",
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       "      <th>8</th>\n",
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       "      <th>9</th>\n",
       "      <td>200</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>0.150961</td>\n",
       "      <td>44.687430</td>\n",
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       "      <th>10</th>\n",
       "      <td>300</td>\n",
       "      <td>800</td>\n",
       "      <td>1</td>\n",
       "      <td>0.199227</td>\n",
       "      <td>1079.709291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>300</td>\n",
       "      <td>700</td>\n",
       "      <td>1</td>\n",
       "      <td>0.154220</td>\n",
       "      <td>179.491695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>300</td>\n",
       "      <td>500</td>\n",
       "      <td>1</td>\n",
       "      <td>0.137502</td>\n",
       "      <td>38.164911</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "      X    Y  Facies  Porosity         Perm\n",
       "0   100  900       1  0.115359     5.736104\n",
       "1   100  800       1  0.136425    17.211462\n",
       "2   100  600       1  0.135810    43.724752\n",
       "3   100  500       0  0.094414     1.609942\n",
       "4   100  100       0  0.113049    10.886001\n",
       "5   200  800       1  0.154648   106.491795\n",
       "6   200  700       1  0.153113   140.976324\n",
       "7   200  500       1  0.126167    12.548074\n",
       "8   200  400       0  0.094750     1.208561\n",
       "9   200  100       1  0.150961    44.687430\n",
       "10  300  800       1  0.199227  1079.709291\n",
       "11  300  700       1  0.154220   179.491695\n",
       "12  300  500       1  0.137502    38.164911"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(df.iloc[0:5,:])                   # display first 4 samples in the table as a preview\n",
    "df.head(n=13)                           # we could also use this command for a table preview"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Summary Statistics for Tabular Data\n",
    "\n",
    "The table includes X and Y coordinates (meters), Facies 1 and 2 (1 is sandstone and 0 interbedded sand and mudstone), Porosity (fraction), and permeability as Perm (mDarcy). \n",
    "\n",
    "There are a lot of efficient methods to calculate summary statistics from tabular data in DataFrames. The describe command provides count, mean, minimum, maximum, and quartiles all in a nice data table. We use transpose just to flip the table so that features are on the rows and the statistics are on the columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
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       "      <th>X</th>\n",
       "      <td>289.0</td>\n",
       "      <td>475.813149</td>\n",
       "      <td>254.277530</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>300.000000</td>\n",
       "      <td>430.000000</td>\n",
       "      <td>670.000000</td>\n",
       "      <td>990.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Y</th>\n",
       "      <td>289.0</td>\n",
       "      <td>529.692042</td>\n",
       "      <td>300.895374</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>269.000000</td>\n",
       "      <td>549.000000</td>\n",
       "      <td>819.000000</td>\n",
       "      <td>999.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Facies</th>\n",
       "      <td>289.0</td>\n",
       "      <td>0.813149</td>\n",
       "      <td>0.390468</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Porosity</th>\n",
       "      <td>289.0</td>\n",
       "      <td>0.134744</td>\n",
       "      <td>0.037745</td>\n",
       "      <td>0.058548</td>\n",
       "      <td>0.106318</td>\n",
       "      <td>0.126167</td>\n",
       "      <td>0.154220</td>\n",
       "      <td>0.228790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Perm</th>\n",
       "      <td>289.0</td>\n",
       "      <td>207.832368</td>\n",
       "      <td>559.359350</td>\n",
       "      <td>0.075819</td>\n",
       "      <td>3.634086</td>\n",
       "      <td>14.908970</td>\n",
       "      <td>71.454424</td>\n",
       "      <td>5308.842566</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          count        mean         std       min         25%         50%  \\\n",
       "X         289.0  475.813149  254.277530  0.000000  300.000000  430.000000   \n",
       "Y         289.0  529.692042  300.895374  9.000000  269.000000  549.000000   \n",
       "Facies    289.0    0.813149    0.390468  0.000000    1.000000    1.000000   \n",
       "Porosity  289.0    0.134744    0.037745  0.058548    0.106318    0.126167   \n",
       "Perm      289.0  207.832368  559.359350  0.075819    3.634086   14.908970   \n",
       "\n",
       "                 75%          max  \n",
       "X         670.000000   990.000000  \n",
       "Y         819.000000   999.000000  \n",
       "Facies      1.000000     1.000000  \n",
       "Porosity    0.154220     0.228790  \n",
       "Perm       71.454424  5308.842566  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().transpose()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Specify the Area of Interest\n",
    "\n",
    "It is natural to set the x and y coordinate and feature ranges manually. e.g. do you want your color bar to go from 0.05887 to 0.24230 exactly? Also, let's pick a color map for display. I heard that plasma is known to be friendly to the color blind as the color and intensity vary together (hope I got that right, it was an interesting Twitter conversation started by Matt Hall from Agile if I recall correctly). We will assume a study area of 0 to 1,000m in x and y and omit any data outside this area."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "xmin = 0.0; xmax = 1000.0               # range of x values\n",
    "ymin = 0.0; ymax = 1000.0               # range of y values\n",
    "pormin = 0.05; pormax = 0.25;             # range of porosity values\n",
    "cmap = plt.cm.plasma                    # color map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualizing Tabular Data with Location Maps¶ \n",
    "Let's try out locmap. This is a reimplementation of GSLIB's locmap program that uses matplotlib. I hope you find it simpler than matplotlib, if you want to get more advanced and build custom plots lock at the source. If you improve it, send me the new code. Any help is appreciated. To see the parameters, just type the command name:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function geostatspy.GSLIB.locmap(df, xcol, ycol, vcol, xmin, xmax, ymin, ymax, vmin, vmax, title, xlabel, ylabel, vlabel, cmap, fig_name)>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GSLIB.locmap"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can populate the plotting parameters and visualize the porosity data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x2bfa7e9f550>"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GSLIB.locmap(df,'X','Y','Porosity',xmin,xmax,ymin,ymax,pormin,pormax,'Well Data - Porosity','X(m)','Y(m)','Porosity (fraction)',cmap,'locmap_Porosity')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Look carefully, and you'll notice the the spatial samples are more dense in the high porosity regions and lower in the low porosity regions.  There is preferential sampling.  We cannot use the naive statistics to represent this region.  We have to correct for the clustering of the samples in the high porosity regions. \n",
    "\n",
    "Let's try cell declustering. We can interpret that we will want to minimize the declustering mean and that a cell size of between 100 - 200m is likely a good cell size, this is 'an ocular' estimate of the largest average spacing in the sparsely sampled regions.   \n",
    "\n",
    "Let's check out the declus program reimplimented from GSLIB."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function geostatspy.geostats.declus(df, xcol, ycol, vcol, iminmax, noff, ncell, cmin, cmax)>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geostats.declus"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now populate the parameters. We will run a very wide range of cell sizes, from 10m to 2,000m ('cmin' and 'cmax') and take the cell size that minimizes the declustered mean ('iminmax' = 1 minimize, and = 0 maximize). Multiple offsets (number of these is 'noff') uses multiple grid origins and averages the results to remove sensitivity to grid position.  The ncell is the number of cell sizes.\n",
    "\n",
    "The output from this program is:\n",
    "\n",
    "* wts - an array with the weigths for each data (they sum to the number of data, 1 indicates nominal weight)\n",
    "* cell_sizes - an array with the considered cell sizes\n",
    "* dmeans - de an "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 289 data with:\n",
      "   mean of      0.13474387540138408 \n",
      "   min and max  0.058547873 and 0.228790002\n",
      "   standard dev 0.03767982164385207 \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Facies</th>\n",
       "      <th>Porosity</th>\n",
       "      <th>Perm</th>\n",
       "      <th>Wts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100</td>\n",
       "      <td>900</td>\n",
       "      <td>1</td>\n",
       "      <td>0.115359</td>\n",
       "      <td>5.736104</td>\n",
       "      <td>3.064286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>100</td>\n",
       "      <td>800</td>\n",
       "      <td>1</td>\n",
       "      <td>0.136425</td>\n",
       "      <td>17.211462</td>\n",
       "      <td>1.076608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>100</td>\n",
       "      <td>600</td>\n",
       "      <td>1</td>\n",
       "      <td>0.135810</td>\n",
       "      <td>43.724752</td>\n",
       "      <td>0.997239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>100</td>\n",
       "      <td>500</td>\n",
       "      <td>0</td>\n",
       "      <td>0.094414</td>\n",
       "      <td>1.609942</td>\n",
       "      <td>1.165119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>0.113049</td>\n",
       "      <td>10.886001</td>\n",
       "      <td>1.224164</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     X    Y  Facies  Porosity       Perm       Wts\n",
       "0  100  900       1  0.115359   5.736104  3.064286\n",
       "1  100  800       1  0.136425  17.211462  1.076608\n",
       "2  100  600       1  0.135810  43.724752  0.997239\n",
       "3  100  500       0  0.094414   1.609942  1.165119\n",
       "4  100  100       0  0.113049  10.886001  1.224164"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wts, cell_sizes, dmeans = geostats.declus(df,'X','Y','Porosity',iminmax = 1, noff= 10, ncell=100,cmin=10,cmax=2000)\n",
    "df['Wts'] = wts                            # add weights to the sample data DataFrame\n",
    "df.head()                                  # preview to check the sample data DataFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at the location map of the weights."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x2bfa6d15898>"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GSLIB.locmap(df,'X','Y','Wts',xmin,xmax,ymin,ymax,0.5,2.5,'Well Data Weights','X(m)','Y(m)','Weights',cmap,'locmap_Weights')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Does it look correct?  See the weight varies with local sampling density?  \n",
    "\n",
    "Now let's add the distribution of the weights and the naive and declustered porosity distributions. You should see the histogram bars adjusted by the weights. Also note the change in the mean due to the weights. There is a significant change."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Porosity naive mean is 0.135.\n",
      "Porosity declustered mean is 0.121.\n",
      "Correction of 0.1002.\n",
      "\n",
      "Summary statistics of the declsutering weights:\n",
      "DescribeResult(nobs=289, minmax=(0.2819756671865989, 3.984325446814365), mean=0.9999999999999996, variance=0.40927076480664726, skewness=1.9395015754905447, kurtosis=4.287460624778004)\n"
     ]
    },
    {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(221)\n",
    "GSLIB.locmap_st(df,'X','Y','Wts',xmin,xmax,ymin,ymax,0.0,2.0,'Declustering Weights','X (m)','Y (m)','Weights',cmap)\n",
    "\n",
    "plt.subplot(222)\n",
    "GSLIB.hist_st(df['Wts'],0.5,2.5,log=False,cumul=False,bins=20,weights=None,xlabel=\"Weights\",title=\"Declustering Weights\")\n",
    "plt.ylim(0.0,60)\n",
    "\n",
    "plt.subplot(223)\n",
    "GSLIB.hist_st(df['Porosity'],0.05,0.25,log=False,cumul=False,bins=20,weights=None,xlabel=\"Porosity\",title=\"Naive Porosity\")\n",
    "plt.ylim(0.0,60)\n",
    "\n",
    "plt.subplot(224)\n",
    "GSLIB.hist_st(df['Porosity'],0.05,0.25,log=False,cumul=False,bins=20,weights=df['Wts'],xlabel=\"Porosity\",title=\"Declustered Porosity\")\n",
    "plt.ylim(0.0,60)\n",
    "\n",
    "por_mean = np.average(df['Porosity'].values)\n",
    "por_dmean = np.average(df['Porosity'].values,weights=df['Wts'].values)\n",
    "\n",
    "print('Porosity naive mean is ' + str(round(por_mean,3))+'.')\n",
    "print('Porosity declustered mean is ' + str(round(por_dmean,3))+'.')\n",
    "cor = (por_mean-por_dmean)/por_mean\n",
    "print('Correction of ' + str(round(cor,4)) +'.')\n",
    "\n",
    "print('\\nSummary statistics of the declsutering weights:')\n",
    "print(stats.describe(wts))\n",
    "\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.0, top=2.5, wspace=0.2, hspace=0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's look at the plot of the declustered porosity mean vs. the declustering cell size over the 100 runs. At very small and very large cell size the declustered mean is the naive mean. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(111)\n",
    "plt.scatter(cell_sizes,dmeans, s=30, alpha = 0.2, edgecolors = \"black\", facecolors = 'red')\n",
    "plt.xlabel('Cell Size (m)')\n",
    "plt.ylabel('Declustered Porosity Mean (fraction)')\n",
    "plt.title('Declustered Porosity Mean vs. Cell Size')\n",
    "plt.plot([0,2000],[por_mean,por_mean],color = 'black')\n",
    "plt.plot([200,200],[0.10,0.16],color = 'black',linestyle='dashed')\n",
    "plt.text(300., 0.136, r'Naive Porosity Mean')\n",
    "plt.text(500., 0.118, r'Declustered Porosity Mean')\n",
    "plt.text(230., 0.154, r'Minimizing')\n",
    "plt.text(230., 0.150, r'Cell Size')\n",
    "plt.ylim(0.10,0.16)\n",
    "plt.xlim(0,2000)\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=1.2, top=1.2, wspace=0.2, hspace=0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The cell size that minimizes the declustered mean is about 200m (estimated from the figure). This makes sense given our previous observation of the data spacing. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Comments\n",
    "\n",
    "This was a basic demonstration of declustering to correct for sampling bias. Much more could be done, I have other demonstrations on the basics of working with DataFrames, ndarrays and many other workflows availble at https://github.com/GeostatsGuy/PythonNumericalDemos and https://github.com/GeostatsGuy/GeostatsPy.\n",
    "\n",
    "I hope this was helpful,\n",
    "\n",
    "*Michael*\n",
    "\n",
    "Michael Pyrcz, Ph.D., P.Eng. Associate Professor The Hildebrand Department of Petroleum and Geosystems Engineering, Bureau of Economic Geology, The Jackson School of Geosciences, The University of Texas at Austin\n",
    "\n",
    "#### More Resources Available at: [Twitter](https://twitter.com/geostatsguy) | [GitHub](https://github.com/GeostatsGuy) | [Website](http://michaelpyrcz.com) | [GoogleScholar](https://scholar.google.com/citations?user=QVZ20eQAAAAJ&hl=en&oi=ao) | [Book](https://www.amazon.com/Geostatistical-Reservoir-Modeling-Michael-Pyrcz/dp/0199731446) | [YouTube](https://www.youtube.com/channel/UCLqEr-xV-ceHdXXXrTId5ig)  | [LinkedIn](https://www.linkedin.com/in/michael-pyrcz-61a648a1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
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